Opening day! When hope springs eternal for every major league baseball fan. Each team is tied for first (and last) place for what will almost assuredly be the final time. Which teams will rise, and which will fall? RotoValue has some predictions. Using the model that forecasts player performance, and aggregating across each roster, I… Continue reading MLB Crystal Ball 2022
Category: Major League Baseball
RotoValue now showing player news from RotoBaller.com
RotoValue is now partnering with RotoBaller.com for player news. Starting this month, we will now be showing RotoBaller player news for both NBA and MLB. This will give better fantasy focused news items for players throughout the site. The main place to see player news on RotoValue is the News pages, which can show news on… Continue reading RotoValue now showing player news from RotoBaller.com
MLB Crystal Ball 2021
Today is opening day, the start of the new season. How will it end up? Using RotoValue player projections for each team, I’ve estimated win totals based on projected runs scored and runs allowed. Here are the standings: AL East Won Lost Pct RS RA Yankees 87.1 74.9 0.538 665 617 Blue Jays 82.1 79.9… Continue reading MLB Crystal Ball 2021
Reverse Platoon Splits – Before and After
Tom Tango asked someone to see what players with at least a 30-point wOBA reverse platoon split in their first 2500 plate appearances did for the rest of their careers, and Sean Foreman kindly provided split data from his database. So I hacked together a Perl script to read his data and analyze it. The script lets… Continue reading Reverse Platoon Splits – Before and After
Professional Standings Now Available on RotoValue
RotoValue now also shows professional standings for both MLB and NBA. And, like the fantasy standings pages, you can customize them to any date range you like. So if you want to see how your team has done since a particular date, or over the past month, or since they called up Gleyber Torres or Ronald Acuna,… Continue reading Professional Standings Now Available on RotoValue
One Player, Two Kinds of Stats: Handling Shohei Ohtani
This year the Angels signed Shohei Ohtani, the young Japanese star who played both as a pitcher and outfielder for the Hokkaido Nippon Ham Fighters of the Japanese Pacific League. As in Japan, Ohtani is expected to continue to play extensively both as a pitcher and hitter. Some players have played significantly at the major league… Continue reading One Player, Two Kinds of Stats: Handling Shohei Ohtani
Comparing Projected HR leaders to actual
Tom Tango asked an interesting question on Twitter yesterday: The odds of the projected HR leader actually leading the league is an interesting question. I’ve been doing projections since 2011, so I thought I’d sweep my database for the RotoValue projections and see what that history was. That gives me just five years, but it… Continue reading Comparing Projected HR leaders to actual
FiveThirtyEight Baseball Division Champs Puzzle
Update: I’ve added a link to the Perl progam I used to do these simulations. Oliver Roeder presents a weekly puzzler on FiveThirtyEight, and this week it was a baseball-themed puzzle. Assume a sport (say, “baseball”) in which each team plays 162 games in a season. Also assume a “division” (e.g. the “AL East”) containing 5 teams, each… Continue reading FiveThirtyEight Baseball Division Champs Puzzle
Comparing 2014 Projections – ERA and WHIP
Yesterday I ran comparisons of several projections systems for an all-inclusive batting statistic, wOBA. Today I’m running the same tests, computing root mean square error (RMSE) and mean absolute error (MAE), for two commonly used fantasy statistics, ERA and WHIP. These tests are bias-adjusted, so what matters is a player’s ERA or WHIP relative to the overall average of that… Continue reading Comparing 2014 Projections – ERA and WHIP
Comparing 2014 Projections – wOBA
In the past three years I’ve done reviews of baseball projections systems with actual data for those systems for which I could get data. Will Larson maintains a valuable site of projections from many different sources, and most of the sources I’m comparing are from that. As in the past, I’m computing root mean square error (RMSE) and mean absolute error (MAE) for… Continue reading Comparing 2014 Projections – wOBA